An acidic residue buried in the dimer interface of isocitrate dehydrogenase 1 (IDH1) helps regulate catalysis and pH sensitivity

Lucas A. Luna1, Zachary Lesecq1, Katharine A. White2, An Hoang1, David A. Scott3, Olga Zagnitko3, Andrey A. Bobkov3, Diane L. Barber4, Jamie M. Schiffer5, Daniel G. Isom6, and Christal D. Sohl1,‡,§

1Department of Chemistry and Biochemistry, San Diego State University, San Diego, CA, 92182 2Harper Cancer Research Institute, Department of Chemistry and Biochemistry, University of Notre Dame, South Bend, IN, 46617 3Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, 92037 4Department of Cell and Tissue Biology, University of California, San Francisco, CA, 94143 5Janssen Research and Development, 3210 Merryfield Row, San Diego, CA, 92121 6Department of Pharmacology, Sylvester Comprehensive Cancer Center, and Center for Computational Sciences, University of Miami, Miami, FL, 33136

Running title: Mechanisms of pH-dependent IDH1 catalysis

‡Correspondence: Christal D. Sohl, Department of Chemistry and Biochemistry, San Diego State University, CSL 328, 5500 Campanile Dr., San Diego, California 92182, Email: [email protected]; Telephone: (619) 594-2053.

§This paper is dedicated to the memory of our dear colleague and friend, Michelle Evon Scott (1990-2020).

Keywords: enzyme kinetics, cancer, tumor metabolism, pH regulation, post- translational modification (PTM), buried ionizable residues

1 Abstract

Isocitrate dehydrogenase 1 (IDH1) catalyzes the reversible NADP+-dependent conversion of isocitrate to α-ketoglutarate (αKG) to provide critical cytosolic substrates and drive NADPH-dependent reactions like lipid biosynthesis and glutathione regeneration. In biochemical studies, the forward reaction is studied at neutral pH, while the reverse reaction is typically characterized in more acidic buffers. This led us to question whether IDH1 catalysis is pH-regulated, which would have functional implications under conditions that alter cellular pH, like apoptosis, hypoxia, cancer, and neurodegenerative diseases. Here, we show evidence of catalytic regulation of IDH1 by pH, identifying a trend of increasing kcat values for αKG production upon increasing pH in the buffers we tested. To understand the molecular determinants of IDH1 pH sensitivity, we used the pHinder algorithm to identify buried ionizable residues predicted to have shifted pKa values. Such residues can serve as pH sensors, with changes in protonation states leading to conformational changes that regulate catalysis. We identified an acidic residue buried at the IDH1 dimer interface, D273, with a predicted pKa value upshifted into the physiological range. D273 point mutations had decreased catalytic efficiency and, importantly, loss of pH-regulated catalysis. Based on these findings, we conclude that IDH1 activity is regulated, at least in part, by pH. We show this regulation is mediated by at least one buried acidic residue ~12 Å from the IDH1 active site. By establishing mechanisms of regulation of this well-conserved enzyme, we highlight catalytic features that may be susceptible to pH changes caused by cell stress and disease.

2 Introduction

Isocitrate dehydrogenase 1 (IDH1) is a highly conserved metabolic enzyme that catalyzes the reversible NADP+-dependent conversion of isocitrate to α-ketoglutarate (αKG) (Fig. 1A). This reversible reaction is important for providing substrates for a host of cytosolic reactions, for anaplerosis or the restocking of the tricarboxylic acid (TCA) cycle, providing reducing power in the form of NADPH, and driving lipid metabolism [1-3]. Given its importance in cell metabolism, it is perhaps unsurprising that changes in wild type (WT) IDH1 expression levels or acquisition of point mutations are important features of some cancers and result in interesting metabolic changes. For example, increased mRNA and protein levels of WT IDH1 are associated with cancer [4-6], including as high as 65% percent of primary glioblastomas [4]. Oncogenic point mutations in IDH1 drive ~85% of lower grade gliomas and secondary glioblastomas, ~12% of acute myeloid leukemias, and ~40% of chondrosarcomas [7-11]. Most mutations affect R132, an active site residue that plays a role in coordinating the C-3-carboxylate of isocitrate [12]. R132H and R132C are by far the most common mutations in IDH1 [5], and these mutations confer two biochemical changes: 1) an inability to catalyze the normal reaction, and 2) facilitation of a neomorphic reaction, the NADPH-dependent conversion of αKG to D-2-hydroxyglutarate (D2HG) [13] (Fig. 1B), an oncometabolite that inhibits αKG-binding enzymes [14, 15]. IDH1 mutants are bona fide therapeutic targets, with the first selective mutant IDH1 inhibitor recently approved for use in the clinic primarily for leukemias [16, 17]. Proteins can be regulated by their environment to respond in real time to cellular needs. In response to stressors such as hypoxia, the reverse reaction catalyzed by IDH1, the reduction of αKG to isocitrate (Fig. 1A) appears to confer resilience [18-20]. However, the mechanism of this metabolic shift is still under debate and may result from slowing the forward reaction [21]. It also remains unclear whether IDH1 (the cytosolic isoform) or IDH2 (the mitochondrial isoform) is the major player in reductive metabolism, with isoform localization, local substrate concentrations, and various mechanisms of regulation all

3 likely complicating the discernment of the relative contributions of IDH1 and IDH2 [19, 20, 22-24]. Cellular pH plays a critical role in regulating protein-protein and protein-ligand interactions, as well as protein stability and activity [25]. Unlike most protein regulatory mechanisms and post-translational modifications (PTMs), protonation is non-enzymatic, does not require ATP, and is rapidly reversible. As such, many cellular processes and human pathologies are regulated by small but meaningful changes in the intracellular pH

(pHi) that are sufficient to alter residue ionization state and protein function. A variety of physiological and pathological cellular processes can cause these shifts in pH. For example, a decrease in pHi can occur during apoptosis [26], immune processes [27], nutrient deprivation [28, 29], and oxidative stress [30, 31], while an increase in pHi is important for cell differentiation [32] and directed cell migration [33]. A decrease in pHi is also associated with neurodegenerative diseases [34, 35], while an increase in pHi coupled with a decrease in extracellular pH (pHe) occurs in tumors to drive migration and metastasis [25, 36-39]. Cellular proteins can function as pH sensors through changes in protonation states of ionizable amino acid residues, allowing these proteins to detect changes in pH. Changes in protonation/deprotonation of these residues lead to biologically relevant changes in protein conformation. Proteins with pH-sensitive residue(s) are known as pH sensors. Histidine residues are natural candidates for sensing pHi changes as their pKa value is already in a physiologically relevant range. However, any ionizable residue (such as D, E, or K) can sense changes in global cellular pH if its pKa value is shifted into the physiological pH range, as each residue’s pKa is a function of its atomic-level protein environment [25, 40]. In fact, large changes in pKa values, ΔpKa, make for stronger pH sensors. The change in Gibbs free energy difference, ΔΔG°, that may be stored within a change in pKa value, ΔpKa, can be as high as ΔΔG° = 1.36 × ΔpKa [41]. Interestingly, simply having a buried K residue in a protein tends to downshift that residue’s pKa to a more physiological range [42]. This may trigger conformational changes as a means of pH-regulated catalysis, or can simply be a mechanism to tune protein stability. As an example of the latter, variants of a staphylococcal nuclease were designed to test the consequences of buried K residues in a model protein system [42]. The majority of the K

4 variants show downshifted pKa values to a more physiological range, with the range of shifted pKa values varying widely (from 5 to 10) [42]. The location of the K mutation appears to affect the degree of pKa value shift due to changes in local environment; for example, interactions with carboxylic acid groups enhanced K pKa value shifts [42]. An extension of this work explores the consequences of K, D, and E mutational variants at a single residue, with each variant having notable changes in pKa values, protein stability, ionizability, and structural conformation [40]. Thus, buried ionizable residues can play a critical role in both protein function, stability, and pH sensing. There is significant diversity among the types of proteins that have been identified as pH sensors, including low molecular weight GTPases [43], G protein α subunits [29], G protein-coupled receptors [44], an Na+-H+ exchanger [45], β-catenin [46], a kinase [47], a guanine nucleotide exchange factor [48], and metabolic enzymes [49-57]. Notable examples of metabolic enzymes include lactate dehydrogenase, whose activity is dependent on pH in part through changes in H residue protonation state that affects substrate binding and catalysis [58, 59], and phosphofructokinase, which exhibits decreased catalytic efficiency driven primarily through an increase in Km as the pH drops [29, 55, 60]. Despite pH-sensing in phosphofructokinase being first described over half a century ago, the mechanisms of pH-sensitive catalysis are still not yet understood. Thus, identifying mechanisms of pH-sensing are challenging, but elucidating such mechanisms can be highly transformative for understanding environment-sensitive protein regulation. There is evidence that IDH1 catalysis is also affected by changes in pH. Rates of NADPH consumption stemming from isocitrate production (the normal reverse reaction, Fig. 1A) by human WT IDH1 increase upon decreasing pH in potassium phosphate (KPhos) [61] and Tris/bis-Tris [62] buffers, though the effects on steady-state kinetic parameters are not reported. Pig IDH2 is sensitive to changes in pH, with increased rates of αKG production observed as pH increases [63]. This appears to be driven in part by ionizability of H319 and H315 IDH2, as H319Q and H315Q (corresponding to H354 and H358 in human IDH2) decreases catalytic efficiency by ~2-fold [63]. However, only the residue corresponding to H354 in IDH2 is conserved in human IDH1 (H315 IDH1), and mutation of this residue to alanine destroys catalytic activity because this residue binds the phosphate of NADP+ [12, 64, 65]. Low pH also increases rates of NADPH

5 consumption in oxen IDH2, and it is suggested that this is driven, at least in part, by better

CO2 solubility at lower pH driving the reverse reaction [66]. Thus, some reactions catalyzed by IDH1 in various organisms appear to be sensitive to pH under select conditions, but a lack of reported steady-state parameters and inconsistent reaction conditions complicate conclusions. Here we present a thorough analysis of IDH1 catalysis at varying pH values and show that the forward reaction appears to be regulated by pH. The kcat of the forward reaction (isocitrate to αKG) shows the most reliable pH dependence in the buffer systems tested here, though the pH-sensitivity of kinetic parameters of the reverse reaction is buffer-dependent. We identified buried networks of acidic and basic residues that included D273 and K217 IDH1, two residues that were calculated to have shifted pKa values into the physiological range. When D273 IDH1 was mutated to non-ionizable residues, there was a drastic loss of activity and decreased sensitivity to pH and, in the R132H IDH1 background, apparent disruption of mutant IDH1 inhibitor binding. Overall, this work uses structural informatics and experimental methods to identify and evaluate a mechanism of pH-dependent catalytic regulation that is mediated, at least in part, by a buried acidic residue found in the IDH1 dimer interface.

Experimental procedures

Materials

Tris-hydrochloric acid, Tris base, bis-Tris, NaOH, NaCl, MgCl2 hexahydrate, dithiothreitol, NADP+ disodium salt, NADPH, KPhos dibasic, KCl, BL-21 Gold (DE3) competent cells, Luria-broth (LB)-Agar, kanamycin sulfate, Terrific broth, IPTG, EDTA-free protease inhibitor tablets, Ni-NTA resin, Dulbecco’s Modified Eagle Medium (DMEM), 2’,7’-bis-(2- carboxyethyl)-5-(and-6)-carboxyfluorescein acetoxymethyl ester, Dulbecco’s phosphate buffered saline (DPBS) and Triton X-100 were all obtained from Fisher Scientific (Hampton, NH). Isocitrate, αKG, and imidazole were obtained from Acros Organics (Fisher Scientific, Hampton, NH). Fetal bovine serum (FBS) was obtained from VWR

6 (Radnor, PA). 5-(N-Ethyl-N-isopropyl)amiloride was obtained from Sigma-Aldrich (St. Louis, MO). ESOM sodium salt was obtained from Apexbio (Houston, TX). Nigericin sodium was obtained from Tocris (Bristol, UK).

Plasmid mutagenesis WT and R132H IDH1 clones were generously provided by Charles Rock (St. Jude’s Hospital). All IDH1 cDNA constructs are in a pET-28b plasmid vector that contains an N- terminal hexahistidine tag. Site-directed mutagenesis was used to generate single point mutations in WT IDH1 using the manufacturer’s (Kappa Biosciences, Oslo, Norway) guidelines with the following primers: D273N (forward primer 5’- TTTATTTGGGCCTGCAAAAACTATAATGGTGATGTTCAGAGC, reverse primer 5’- GCTCTGAACATCACCATTATAGTTTTTGCAGGCCCAAATAAA); D273L (forward primer 5’-TGGTTTTATTTGGGCCTGCAAAAACTATCTGGGTGATGTTCAGAGCGA, reverse primer 5’- TCGCTCTGAACATCACCCAGATAGTTTTTGCAGGCCCAAATAAAACCA); D273S (forward primer 5’- GTGGTTTTATTTGGGCCTGCAAAAACTATAGTGGTGATGTTCAGAG, reverse primer 5’-CTCTGAACATCACCACTATAGTTTTTGCAGGCCCAAATAAAACCAC); K217M (forward primer 5’- CTGAGCACCAAAAATACCATTCTGATGAAATACGATGGTCGCTTTAAAGATA, reverse primer 5’- TATCTTTAAAGCGACCATCGTATTTCATCAGAATGGTATTTTTGGTGCTCAG); K217Q (forward 5’- CTGAGCACCAAAAATACCATTCTGCAGAAATACGATGGTCGCTTTAAAGAT, reverse primer 5’- ATCTTTAAAGCGACCATCGTATTTCTGCAGAATGGTATTTTTGGTGCTCAG). Site- directed mutagenesis was also used to generate single point mutations in the R132H IDH1 background according to the manufacturer’s guidelines (Kappa Biosciences, Oslo, Norway) using the following primers: D273N (forward primer 5’- TTTATTTGGGCCTGCAAAAACTATAATGGTGATGTTCAGAGC, reverse primer 5’- GCTCTGAACATCACCATTATAGTTTTTGCAGGCCCAAATAAA); D273L (forward

7 primer 5’-TGGTTTTATTTGGGCCTGCAAAAACTATCTGGGTGATGTTCAGAGCGA, reverse primer 5’- TCGCTCTGAACATCACCCAGATAGTTTTTGCAGGCCCAAATAAAACCA); D273S (forward primer 5’- GTGGTTTTATTTGGGCCTGCAAAAACTATAGTGGTGATGTTCAGAG, reverse primer 5’-CTCTGAACATCACCACTATAGTTTTTGCAGGCCCAAATAAAACCAC). All constructs were sequenced to confirm accuracy.

Protein purification WT and mutant IDH1 homodimers were expressed and purified as described previously (> 95% purity) [67]. Briefly, BL21-Gold (DE3) E. coli cells transformed with the proper IDH1 construct were incubated at 37 ˚C to an OD600 of 1.0-1.2. The cultures were then induced with a final concentration of 1 mM IPTG and incubated for 18-20 hours at 18 ˚C. IDH1 protein was purified using Ni-NTA column chromatography, and flash frozen in liquid nitrogen for storage at -80˚C for ≤1 month. To ensure that WT and mutant IDH1 dimerized to a similar degree, WT and R132L IDH1 were analyzed using size exclusion chromatography (SEC) and were both found to be primarily in the dimer form (Fig. S1). Steady-state activity assays¾ The activity of IDH1 homodimers was assessed at 37 ˚C using steady-state methods described previously [67] [62]. The Tris-based assays were prepared as follows: for the conversion of isocitrate to αKG for pH >7, a cuvette containing assay buffer (50 mM Tris buffer ranging from pH 8.0 to 7.2 at 37˚C, 150 mM

NaCl, 10 mM MgCl2, 0.1 mM dithiothreitol), and 100 nM WT IDH1, were preincubated for 3 minutes at 37 ˚C. For the conversion of isocitrate to αKG for pH ≤7.0 a cuvette containing assay buffer (50 mM bis-Tris ranging from pH 7.0 to 6.2 at 37˚C, 150 mM NaCl,

10 mM MgCl2, 0.1 mM dithiothreitol), and 100 nM WT IDH1 were preincubated for 3 minutes at 37 ˚C. For the conversion of αKG to isocitrate for pH >7 [62], a cuvette containing assay buffer (50 mM Tris ranging from pH 8.0-7.2 at 37 ˚C, 150 mM NaCl, 10 mM MgCl2, 66 mM NaHCO3), and 100 nM WT IDH1, were preincubated for 3 minutes at 37 ˚C. For the conversion of αKG to isocitrate for pH ≤7.0, a cuvette containing assay buffer (50 mM bis-Tris pH ranging 7.0-6.2 for 37˚C, 150 mM NaCl, 10 mM MgCl2, 66 mM

NaHCO3) and 100 nM WT IDH1, were preincubated for 3 minutes at 37 ˚C.

8 The KPhos buffer-based assays were prepared as follows: for the conversion of isocitrate to αKG, a cuvette containing assay buffer (50 mM KPhos ranging from pH 8.0-

6.2 at 37 ˚C, 150 mM KCl, 10 MgCl2, 0.1 mM dithiotheitol), and 100 nM IDH1 were preincubated for 3 minutes at 37˚C. For the conversion of αKG to isocitrate, a cuvette containing assay buffer (50 mM KPhos pH ranging from 8.0-6.2 at 37 ˚C, 150 mM KCl,

10 mM MgCl2, 66 mM NaHCO3, and 0.1 mM dithiothreitol), and 100 nM IDH1, were preincubated for 3 minutes at 37 ˚C. The pH of αKG was adjusted to the pH of the assay before use. In reactions measuring isocitrate to αKG conversion, reactions were initiated by adding NADP+ and isocitrate, with saturating NADP+ and titrating in various concentrations of isocitrate. In reactions measuring αKG to isocitrate conversion, or αKG to D2HG conversion, reactions were initiated by adding NADPH and αKG, with saturating NADPH and titrating in various concentrations of αKG. In all cases, the change in absorbance due to changing NADPH concentrations was monitored at 340 nm. For all reactions, the slope of the linear ranges of the assays were calculated and converted to µM NADPH using the molar extinction coefficient for NADPH of 6.22 cm-1 -1 -1 mM to obtain kobs (i.e. µM NADPH/µM enzyme s at each substrate concentration). Results were fit to hyperbolic plots in GraphPad Prism (GraphPad Software, La Jolla, CA) to estimate kcat and Km values ± SE.

Thermal stability using circular dichroism The stability of WT IDH1 in the pH range from 8.0-6.2, and D273L IDH1 at pH 7.5 were assessed using circular dichroism (CD) as described previously [67]. Briefly, IDH1 was diluted to 5 µM in a buffer containing 10 mM KPhos buffer at desired pH and 100 mM KCl. The thermal melt experiment was initiated at 20 ˚C and the temperature was increased to 70 ˚C in 1˚C increments. The secondary structure of IDH1 is rich in α helices and was monitored via the 222 nm peak, corresponding to α-helicity. Analysis was performed using GraphPad Prism (GraphPad Software, La Jolla, CA) with a Boltzmann sigmoidal fit [68]. pHinder algorithm

9 The details of the pHinder algorithm have been described previously [29, 43, 69]. Briefly, protein structures were downloaded from the Protein Data Bank (PDB) and the pHinder program was used to calculate ionizable residue networks using a two-step procedure. First, a Delaunay triangulation was calculated using the terminal side-chain atoms of all ionizable residues (D, E, H, C, K, R) and minimized by removing network edges longer than 10 Å. This triangulation was further simplified by removing redundant network connections. Second, using a molecular surface calculated by the pHinder algorithm, each ionizable network residue was classified as buried (>3.0 Å below the surface), margin (<3.0 Å below and <1.0 Å above the surface), or exposed (>1.0 Å above the surface). Depth of burial was determined by measuring the minimum distance between the ionizable group and the triangular facets of the pHinder-calculated surface. Buried networks were identified as contiguous runs of buried residues. Acidic and basic networks were identified as contiguous runs of each residue type.

ITC measurements Isothermal titration calorimetry (ITC) was performed in Sanford Burnham Prebys Protein Analysis Core using a Low Volume Affinity ITC calorimeter (TA Instruments). 3.0 to 6.0 µl aliquots of solution containing 0.15 mM AGI-5198 or ML309 were injected into the cell containing 0.03 to 0.05 mM protein. 20 injections were made. The experiments were performed at 23 ˚C in buffer containing 20 mM Tris pH 7.5, 100 mM NaCl, 2 mM β- mercaptoethanol, and 0.2 mM NADPH. Baseline control data were collected injecting ligand into the cell containing buffer only. ITC data were analyzed using Nanoanalyze software provided by TA Instruments.

Computational methods PROPKA [70, 71] was used to predict the protonation states in the PDB 1T0L structure [72] as described previously. For basic structural modeling of the mutants, due to structural similarity in the mutant and WT IDH1 holo forms, and instability of the α10 helix in the mutant IDH1 structures, the WT background was selected for basic modeling. PDB 1T0L and 1T09 structures [72] were used to generate models of D273N, D273L, and D273S in the WT IDH1 apo (NADP+ bound) and holo (isocitrate, NADP+, and Ca2+)

10 backgrounds. Mutations were made using Coot software [73], and Geometry Minimization in the Phenix software suite [74] was used to regularize geometries of the ligands and protein chains. 500 maximum iterations and 5 macrocycles were used, with bond lengths, bond angles, nonbonded distances, dihedral angles, chirality, parallelity, and planarity considered.

Cellular pHi modulations HT1080 cell lines were all cultured in DMEM with 10% FBS and incubated at 37

˚C with 5% CO2. The effects of proton pump inhibitors on pHi was evaluated in triplicate by first adding 0.3x105 cells per well in a 24-well plate and incubated overnight. The following day the proton pump inhibitor ESOM was dissolved in PBS and was added to the cells (200 µM final concentration), and the cells were again incubated at 37˚C 5%

CO2. After 16-24 hours, the pHi was read by first loading cells with 1 μM BCECF-AM dissolved in DMSO (final cellular concentration of DMSO at 0.1%) at 37 ˚C at 5% CO2 for 15 minutes. Excess dye was removed by washing cells 3 times with bicarbonate buffer

(25 mM bicarbonate, 115 mM NaCl, 5 mM KCl, 10 mM glucose, 1 mM MgSO4, 1 mM

KHPO4 pH 7.4 at 37 ˚C, and 2 mM CaCl2) with ESOM to preserve pHi manipulation conditions. After the wash steps, the fluorescence intensity of the BCECF-AM probe was detected with dual excitation (490 nm and 440 nm) and a fixed emission wavelength of

535 nm. Fluorescence ratios (490 nm/440 nm) were converted to pHi values by calibrating each experiment with a standard curve ranging from pH 6.5 to 7.5 using 25 mM HEPES, 105 mM KCl, and 1 mM MgCl2 and 10 μM nigericin to equilibrate pHi with pHe. Metabolites were derivatized and quantified using GC-MS as described previously [75].

Results

Effects of pH modulation on WT IDH1 activity

11 Heterologously expressed and purified human IDH1 was characterized under steady-state parameters to determine the effects of pH on catalysis. The kcat values of the forward reaction, isocitrate to αKG, in both KPhos and Tris/bis-Tris buffers were pH dependent, exhibiting trends that increased with increasing pH. However, variability in Km values minimized these trends when comparing catalytic efficiencies (Fig. 2, Table 1), suggesting substrate titration may also affect catalysis. The reverse reaction catalyzed by human WT IDH1 was generally much less efficient than the forward reaction, resulting primarily from a decrease in kcat but also from an increase in Km, particularly in KPhos buffer (Fig. 2C-G). Here, any pH dependence observed was primarily limited to studies in Tris/bis-Tris buffers, as only a very slight trend was seen in kcat in KPhos buffer. Modest decreases in Km at more acidic pH values were observed primarily in Tris/bis-Tris buffers, and limited effects on kcat meant this small trend was also seen when comparing catalytic efficiencies (Fig. 2E-G, Table 1). pH-dependent trends for the reverse reaction were relatively small and showed much greater buffer-to- buffer variability. To ensure that changes in activity were not due to protein unfolding, we used CD to show that IDH1 secondary structure features remained stable through this range of pH values, with no significant change in Tm value (Fig. S2). Thus, from our steady-state assessment, we concluded that the pH dependence of kcat for the forward reaction had the most consistent trend in our assay conditions compared to the reverse and neomorphic reactions, which had more modest trends and were typically buffer- dependent. Consequently, the forward reaction became the major focus of our consequent characterization.

Modulation of pH in cell lines Small but meaningful changes in intracellular pH can occur during a variety of cellular processes like apoptosis [26], under changing environments like hypoxia [76], and in disease states like neurodegenerative diseases [34, 35], cancer [25, 36-39], and diabetes [77]. Since an increase in pH led to increased kcat values for the forward reaction in biochemical assays with WT IDH1, we sought to determine if acidic cellular environments led to changes in IDH1-relevant metabolite levels.

12 We modulated the cellular pHi by treating cells with proton transport inhibitors or ion exchange inhibitors [78, 79] and then quantified metabolite levels in cells using gas chromatography coupled to mass spectrometry (GC/MS). These experiments were admittedly limited since several metabolic pathways affect isocitrate and αKG levels. In an attempt to mitigate this, we selected isogenic cell lines that had varying levels of WT IDH1: patient-derived HT1080 cells containing either an endogenous heterozygous R132C mutation (R132C/+ IDH1, where + denotes WT IDH1) or with an R132C-ablated version of this cell line that also stably overexpresses WT IDH1 (-/+++ IDH1) [80]. As a result of the R132C IDH1 mutation, D2HG is produced and WT IDH1 activity is ablated in protein expressed from this allele [22, 81, 82]. A series of proton transport inhibitors, including esomeprazole (ESOM), which targets proton pumps like V-ATPase, and ion exchange inhibitors 4,4’-diisothiocyano-2,2’-stilbenedisulfonic acid (DIDS) and 5-(N- ethyl-N-isopropyl)amiloride (EIPA), were tested at varying concentrations to find the most effective methods to decrease pHi without causing an observed increase in cell death (Fig. S3). For the HT1080 cell lines, treatment with 200 µM ESOM was most effective in meeting these goals (Table 2, Fig. 3A). Isocitrate levels significantly dropped upon ESOM treatment in HT1080 cells (Table 2, Fig. 3B), though these values were near the limit of detection. αKG also decreased upon a shift to an acidic pHi in HT1080 cell lines (Table 2, Fig. 3B), though significance wasn’t achieved in the case of the HT1080 -/+++ IDH1 cells. A decrease in

αKG concentration was not surprising due to the observed decrease in kcat in more acidic buffers, though of course many enzymes contribute to αKG levels, including IDH2 and IDH3. Notably, a global decrease in metabolite concentrations was not observed; fifty common metabolites were quantified in each of the cell lines, and ESOM treatment yielded both increases and decreases in metabolite levels (Table S1), minimizing the possibility that cells were simply in the process of dying. 2HG levels in the mutant cell line (the D and L isomers of 2HG cannot be resolved in these experiments), though not a focus in this work, were also noted to decrease upon ESOM treatment.

Characterizing IDH1 ionizable networks

13 To explore possible mechanisms for the pH dependence observed in the forward reaction catalyzed by IDH1, we used a structural informatics approach known as pHinder [29, 43, 69] to identify potential pH-sensing ionizable residues. Briefly, the pHinder algorithm uses triangulation to calculate topological networks of ionizable residues (D, E, H, C, K, and R) in proteins. These networks identify characteristics that can be predictive of protein structure-function relationships. For example, portions of ionizable networks buried inside proteins or that comprise contiguous stretches of acidic or basic residues tend to contain residues with pKa values shifted to the physiological pH range (pH 5 to 8). Small changes in pH may then be sensed by these residues via a change in their ionization state, resulting in structural and thus functional changes [28, 29, 51, 83]. We identified a striking number of buried acidic and basic residue networks in structures of WT IDH1 complexed to NADP+ (apo, 1T09 [72]), WT IDH1 bound to NADP+, isocitrate, and Ca2+ (holo, 1T0L [72]), and R132H IDH1 bound to αKG, NADPH, and Ca2+ (holo, 4KZO [64]) (Figs. 4, S4). Here, Ca2+ mimics the catalytic Mg2+ metal required for catalysis. Here, we use the nomenclature of X###, where X refers to the single amino acid code for the WT residue present at residue number ###. As IDH1 is a dimer, we will distinguish the two polypeptide chains by using X### and X###’. Mutations will be noted as X###Y, where X at position ### becomes mutated to Y. Of note, in the holo form of WT IDH1, a short acidic network involving buried residues D275, D273, D273’, and D275’ IDH1 traversed through the middle of the IDH1 dimer (Figs. 4B, S4). Residues D275 and D275’ in IDH1 are involved in ligand and metal binding, but D273 and D273’ are too distant for any direct interactions with substrates (Fig. 4D). In the apo form of WT IDH1 (1T09 [72]), D273 and D273’ were the only amino acids making up a very short network chain, though interestingly R132 in one chain localized to a similar position as D273 in the holo structure (Fig. S4B). Given the unusual number and complexity of the buried ionizable networks in IDH1, we chose to focus on two networks, a short acidic network that traversed through the middle of the IDH1 dimer, and a longer basic network within each IDH1 monomer (Figs. 4, S4). The core component of the short acidic network involves residues D273 and D273’. These residues are found at the dimer interface of IDH1, far from the enzyme active site and close to where allosteric mutant IDH1 inhibitors bind (Fig. 4F). The D273

14 residues also participated in a longer network involving D253, D273’, D279, D273, D252, D252’, D253’, and D279’ in the structure of the holo R132H IDH1 (4KZO [64]) (Fig. 4E), though D275 was no longer involved. In contrast to the short acidic network, we also identified a longer basic network consisting of K151’, H170’, R140, K65, K93, K217’, K212’, R49, and K72 IDH1 in holo WT IDH1 (1T0L [72]), Fig. 4B). This long basic network intersected with the active site, as K212’ is a catalytic residue. Some side chains in the network were buried deeply while other residues were partially exposed. To avoid direct mutational effects on IDH1 catalytic activity (i.e., directly affecting substrate binding or chemistry), we focused our attention on one of the most deeply buried side chains, K217’, that was more distant from the active site (Fig. 4C). The A-chain K217 residue also appeared in an additional network containing 11 amino acids (R100’, H170, K217, R132’, K93’, R109’, R140’, R49’, K58’, K72’, and K212 IDH1), which involved most of the same residues in the opposite chains except R100, R109, R132 (all metal/substrate coordinating residues), and K58; instead K151’ and K65 were included (Fig. 4B). Having selected D273 and K217 residues for in-depth analysis, we next calculated the pKa value of each residue in the WT IDH1 structure (1T0L [72]) using PROPKA [70, 71]. The objective of these calculations was to provide a rough estimate of the D273 and

K217 pKa values (Table S2). K217 had a calculated pKa value of 7.97, while K217’ had a calculated pKa value of 8.24. This indicated downshifts towards more acidic, physiologically-relevant pKa values, consistent with previous findings that buried K residues can have downshifted pKa values that can tune protein stability [40, 42]. D273 and D273’ were also predicted to have more physiologically relevant pKa values, with upshifts to 6.59 and 6.4, respectively. Both of these residues, like much of IDH1, are conserved among many species.

Based on our observations using structural informatics and pKa calculations, we hypothesized that D273 and K217 in IDH1 had features consistent with pH-sensing residues, namely buried ionizable side chains with pKa values shifted to more physiological ranges. Of note, unlike K, D, and E residues, R residues have not been observed to have pKa value shifts when buried [84]. Indeed, we show minimal changes in pKa in R residues (Table S2). As a result of these cumulative findings, we sought to

15 confirm the role of D273 and K217 in IDH1 catalysis in both biochemical and cell-based experiments. Residue K217 in IDH1 has only a modest role in catalysis¾ We first ablated the ability of the D273 and K217 residues to undergo changes in ionization state. K217 IDH1 is found in a loop located between the β10 β-sheet and α7 α-helix, ~8-10 Å from isocitrate depending on the chain (Fig. 4C). As this residue in both monomer chains was predicted to have a downshifted pKa value from ~10.7 in solution to 7.97 and 8.24, we selected mutations that would introduce minimal structural/steric changes but ablate ionizability. Methionine, a nonpolar residue, and Q, a polar uncharged residue, were selected. Recombinant K217M and K217Q IDH1 were heterologously expressed and purified from E. coli, and we measured the catalytic efficiency of the conversion of isocitrate to αKG in steady-state kinetic conditions. K217M IDH1 had no effect on kcat and a modest increase in Km, yielding only a 2.2-fold decrease in catalytic efficiency (Fig. 5A, Table 3). K217Q was more disruptive, with a 5.4-fold decrease in catalytic efficiency driven primarily through a 4-fold increase in Km (Fig. 5A, Table 3). Overall, ionizability at this residue did not appear vital for catalysis, though its mutation did affect activity.

Residue D273 in IDH1 appears to play a role in pH-regulated catalysis and inhibitor binding

D273 in IDH1 was predicted to have an upshifted pKa from a standard value of ~3.7 in solution to a more physiologically relevant value of ~6.5. This residue is located in the first third of the α10 helix, an important regulatory domain that transitions from an ordered loop in the apo form of IDH1 to a helix in the holo form [72]. This residue is ~12 Å from the nearest substrate (isocitrate) and is found at the dimer interface (Fig. 4D). Again, mutations were selected that would minimally disrupt the overall structure but would destroy ionizability, and thus D273N, D273L, and D273S IDH1 were generated. To confirm no major changes in protein folding resulted, we assessed secondary structure of D273L IDH1 using CD, and saw no notable changes in Tm compared to WT IDH1 (Fig. S5). After heterologously expressing and purifying all mutants, we found that the kinetic profile of αKG production (the normal forward reaction) was severely affected (Fig 5B, Table 3). Insertion of a nonpolar residue at this position had very drastic effects, with

16 D273L IDH1 exhibiting a ~170-fold decrease in catalytic efficiency, driven by a 5.4-fold decrease in kcat and 31-fold increase in Km. Interestingly, the more conservative D273N and D273S IDH1 mutations had even more deleterious effects. D273N IDH1 had a >500- fold decrease in kcat/Km, driven primarily through >300-fold increase in Km. D273S IDH1 had a similar effect on kcat and Km as D273N IDH1 (~2.5-fold and nearly 200-fold decreases, respectively, relative to WT IDH1). Thus, D273 IDH1 mutations produced very drastic decreases in catalytic efficiency for the forward reaction as compared to WT IDH1. To determine whether mutation of the D273 residue in IDH1 affected the observed pH sensitivity, we measured the rates of isocitrate to αKG conversion by D273L IDH1 at saturating concentrations of substrates in KPhos buffer at pH 6.5, 7.0, 7.5, and 8.0 (Fig. + 5C). Incubating WT IDH1 with 600 µM isocitrate and 200 µM NADP yielded kobs of 23.0, 27.5, 37.6 and 39.2 s-1 respectively, showing clear trends in pH dependency. In contrast, D273L IDH1 catalysis was not altered by changes in pH (i.e. was insensitive to pH), -1 except at the most acidic environment; kobs rates of 4.5, 6.4, 6.4, and 6.3 s at pH 6.5, 7.0, 7.5, and 8.0, respectively, were observed (Fig. 5C), supporting our hypothesis that D273 is a critical mediator contributing to physiological pH sensitivity. The α10 regulatory domain has been posited to be important for conferring selectivity for mutant IDH1 inhibitor binding [85]. As D273 is located in this domain, we next asked if D273 mutants altered catalysis and inhibitor binding in the R132H IDH1 background. Double mutants (D273N/R132H, D273S/R132H, and D273L/R132H IDH1) were expressed and purified, and the steady-state rates of conversion of αKG to D2HG were measured. However, these double mutants were essentially catalytically inactive. -1 Thus, we only report a limit of detection, kobs, of ≤0.02 s , as measured rates fell below this value. Rates were below the detectable limit despite sampling a range of enzyme concentrations (up to 500 nM) across 4 different recombinant protein preparations with high substrate concentration (up to 5 mM αKG) (Table 3) to improve detection of product formation. This low activity precluded our determination of Km, kcat/Km, or IC50 measurements. Instead, we used isothermal titration calorimetry (ITC) to determine the affinity of D273L/R132H IDH1 for two commercially available selective mutant IDH1 inhibitors, AGI-5198 [86] and ML309 [81]. Interestingly, both inhibitors showed that binding was affected. We measured a Kd of 3.3 +/- 0.5 µM for AGI-5198 binding to IDH1

17 D273L/R132H IDH1 (compared to previously reported IC50 value of 0.07 µM for R132H IDH1 [86]). Under the conditions of our experiments, no binding of ML309 to

D273L/R132H IDH1 was detected, which implied no binding or binding with a Kd ≥ 20 µM due to limits of detection (versus previously reported Kd value of 0.48 ± 0.05 µM for R132H

IDH1[87]) (Table 3). Thus, a ~40-fold or higher increase in Kd was measured for binding of both inhibitors to D273L/R132H IDH1. In sum, this indicates that D273 plays in important role in WT and mutant IDH1 catalysis, pH-sensing in catalysis of the forward normal reaction, and in mutant IDH1 inhibitor binding.

Discussion

Here we report an assessment of the effects of pH on IDH1 catalysis. We show that WT IDH1 is sensitive to pH in catalyzing the forward reaction (Fig. 2), though increases in kcat as the pH increases are mitigated by some corresponding increases in

Km, leading to essentially no pH-dependence when considering catalytic efficiency

(kcat/Km, Table 1). As mammalian cellular concentrations of isocitrate are near the Km values we report, it is possible that local concentrations of isocitrate would support rates near kcat [88], making this a physiologically relevant finding. Only the reverse reaction performed in Tris/bis-Tris buffer showed pH-dependence in catalytic efficiency (Table 1). The buffer-dependence of these findings suggests that previous reliance on a decrease in pH to drive the reverse normal reaction (αKG to isocitrate) by us and others [62] is an effective in vitro strategy for studying catalytic features of IDH1. However, it is likely not appropriate to extrapolate that local changes in cellular pH affect rates of the reverse reaction as physiological cellular changes in pH may be too narrow. It has previously been shown that hypoxia is effective at driving lipid biosynthesis via isocitrate production by IDH1 [18]. In addition to low oxygen content, hypoxia is associated with a decrease in local pHi (for example, [89-91]). However, based on our data, we predict factors other than pH-regulated catalysis are driving switching to reductive metabolism. This may include changes in substrate levels, regulation of IDH1 function as a result of hypoxia, etc.

18 There have been other reported cases of metabolic enzymes having buffer- dependent activities. For example, it has been posited that inorganic phosphate can activate fumarase at higher concentrations, and inhibit this enzyme at concentrations <5 mM [92, 93]. Our experiments did not test whether phosphate acts as an allosteric activator in IDH1, though this will be an interesting future direction to explore. Certainly, generating CO2 as a substrate as required to study the reverse reaction can affect pH if buffering capacity is not sufficient. Further, and perhaps more importantly, CO2 may react with the amines of Tris and bis-Tris buffers [94], affecting the local concentration of CO2 available to drive the reverse normal reaction. Of note, our buffer testing was limited to KPhos and Tris-based buffers, examples of inorganic and non-inorganic ionic buffers. We did not include zwitterionic buffers like HEPES or MOPS, which can have superior buffering capacity in cell-based studies. However, unlike KPhos and Tris buffers, HEPES and MOPS are more redox-sensitive, and thus can introduce new challenges when studying redox-sensitive reactions. However, future work should include these buffering systems. In addition to the acid and base chemistry required for IDH1 catalysis [95, 96], the ionization state of the substrates themselves are important for binding. This can also be playing a role in the results reported here. In IDH purified from pig heart (isoform not specified), isocitrate preferably binds when isocitrate has all three carboxyl groups ionized (deprotonated) [97-100]. It will be interesting to explore in future work if the wide variation in Km values we observe (Fig. 2) is related to this issue of altered ionic form of the substrates. The use of steady-state kinetics in this work to investigate pH sensitivity means that we are examining the role of pH on the overall rate-limiting step (predicted to be hydride transfer [95, 96, 101, 102]), but are potentially missing any sensitivity to pH in non-rate-limiting steps. In order to probe the role of pH in additional steps of catalysis, pre-steady-state kinetic methods would be required, which would be an interesting future direction. There is precedence for pH sensitivity in NADP(H)-dependent hydride transfer reactions; for example, E. coli dihydrofolate reductase (DHFR) is an interesting case where the rate-limiting step changes from product release at low pH to hydride transfer

19 at high pH [103], with hydrogen bonds in key loop conformations driving much of these observations [104-107]. Using the structural informatics program pHinder, we identified the buried ionizable residues K217 and D273 in IDH1 as candidates for having pH-sensing properties. Experimentally, we found that the ionizability of D273 affected both catalysis and pH sensitivity. This was not the case for K217, which we speculate is likely more important for tuning protein stability as described previously for buried K residues in other proteins [40, 42]. These findings demonstrate the advantage of combining structural informatics with experimental validation. Importantly, these findings also confirm the consistent utility of the pHinder algorithm for identifying ionizable residues that are unexpectedly important for both pH sensing and protein function, as D273 is quite distant from the active site. As a result, its importance in IDH1 function would be difficult to predict by other means. Indeed, in this case, we identified a possible role for D273 in pH-sensitive catalysis, supported by our data showing loss of pH-dependent catalysis for the D237L IDH1 mutant in physiologically relevant ranges. As a drop in kcat was only observed at pH 6.5 for D273L, catalysis at even lower pH values could be tested, though low pH values lose physiological relevance and may adversely (and artifactually) affect protein stability. More importantly, we feel exploring additional D273 mutants such as D273E to identify the requirement for a titratable carboxylate residue at this position as a requirement for pH- sensing would be worthy of future exploration. D273 is conserved in IDH1 and IDH2 (D312 IDH2) and is found in the a10 regulatory domain (using IDH1 nomenclature) [72]. According to simple modeling, mutational variants D273N, D173S, and D273N are not predicted to drastically affect either the global structure of IDH1 (Fig. S6) or even local folding features (Fig. S6B, S6C). The regulatory role of this domain likely differs when comparing WT and mutant IDH1, where in the latter form of the protein, unraveling of the a10 helix [85] and changes in water dynamics [87] have been posited to contribute to selectivity of inhibitor binding to mutant over WT IDH1. In contrast, in structures of mutant IDH2, this domain remains in the helical conformation in apo, holo, and inhibitor-bound forms [85, 108]. Interestingly, the D273 homolog in IDH2, D312, is located on the same side of the helix and is only 5.3 Å from Q316 IDH2, a residue involved in acquired resistance to mutant IDH2 inhibitor

20 binding. Q316E IDH1 has been identified in patients treated with the selective mutant IDH2 inhibitor Enasidenib [108], and results in resistance to this drug [109]. Thus, our reported decrease in affinity for mutant IDH1 inhibitors is not surprising when considering the proximity of D273 to the allosteric pocket (Fig. S6D). To extend our biochemical studies, we were interested in studying how changes in pHi affected cellular αKG and isocitrate levels. Based on our kinetic data, our observation that HT1080 cells show a decrease in αKG levels upon a decrease in pHi is unsurprising, though of course there are many sources of αKG production and consumption in addition to what is generated by IDH1. There are also a host of regulatory strategies to modulate levels of this metabolite. For example, in studies exploring the consequences of pHi changes in porcine kidney cells, acidosis results in a decrease of αKG concentration, while alkalosis causes an increase [110]. α-Ketoglutarate dehydrogenase is regulated by pH, with Km values decreasing and kcat values remaining relatively constant as the pH decreases. Thus, it is possible that acidic pH has a more potent effect on α-ketoglutarate dehydrogenase activity relative to IDH1 [111]. To better isolate the cellular changes in isocitrate and αKG levels resulting from altered IDH1 activity upon a decrease in pHi, metabolic flux analysis studies in a series of IDH1 knockout and IDH1-amplified cell lines would be required [18, 112]. While we focus in this work on the reactions catalyzed by WT IDH1, we do note that levels of 2HG decreased upon ESOM treatment. WT lactate dehydrogenase 1 and WT malate dehydrogenase 2 moonlighting activity of L-2HG production increases with decreasing pH [50, 61], though production of D2HG by WT IDH1 does not appear to be dependent on pH [50]. Thus, we were surprised to see a decrease in 2HG production. Of course, cell lines, especially cancer cell lines, have their own unique metabolic rewiring at play, and likely vary greatly in the regulation or production of 2HG pools. Furthermore, these metabolic addictions can change based on available nutrients, genetic profile, gene regulation, etc. An important future direction will be to assess the role of pH in regulating mutant IDH1 catalysis and resulting metabolite flux inside cells. We also consider the possibility that treatment with proton pump inhibitors like

ESOM can affect cells beyond simply lowering pHi. A possible consequence of ESOM treatment includes an increase in autophagy in some cell lines [113]. We do note several

21 amino acid levels are increased upon ESOM treatment (Table S1). Interestingly, some of the largest changes in amino acid composition are in the branched chain amino acids (L, I, V) in WT IDH1-expressing cell lines (Table S1). αKG and other α-keto acids are important for generating branched chain amino acids, and thus our observed depletion of αKG upon ESOM treatment may be related to increased branched chain amino acid synthesis [114]. Overall, our findings characterize the pH sensitivity of human IDH, showing that the kcat of the forward reaction appears most sensitive to changes in pH. Moreover, we identify one residue, D273, that appears to sense these changes in pH by affecting catalysis. Critically, mutation of this residue ablates pH sensitivity. This work is important to further elucidate the mechanisms of human IDH1 catalysis and to clarify its regulation in distinct cellular microenvironments related to normal processes and disease. This work applies structural informatics and biochemical characterization to identify new residue clusters that play a novel functional role in regulating human IDH1 catalysis.

Abbreviations CD, circular dichroism; E. coli, Escherichia coli; DIDS, 4,4’-diisothiocyano-2,2’- stilbenedisulfonic acid; DMEM, Dulbecco’s Modified Eagle Medium; DPBS, Dulbecco’s phosphate buffered saline; EIPA, 5-(N-ethyl-N-isopropyl)amiloride; ESOM, esomeprazole; FBS, Fetal bovine serum; GTP, guanosine triphosphate; IDH, isocitrate dehydrogenase; IPTG, isopropyl β-d-1-thiogalactopyranoside; kDa, kilodaltons; αKG, α- ketoglutarate; KPhos, potassium phosphate; NADPH, ß-nicotinamide adenine dinucleotide phosphate reduced; NADP+, ß-nicotinamide adenine dinucleotide phosphate; N.D., not detected; ns, non-significant; PDB, protein databank; pHi, internal pH; pHe, external pH; SEC, size-exclusion chromatography; S.E.M, standard error of the mean; WT, wild type; GC/MS, gas chromatography/mass spectrometry

Author contributions LAL and ZL performed the kinetic assays. LAL prepared cDNA constructs and performed the cellular pH modulation assays and CD measurements. KAW and DLB aided in the design of the cellular pH modulation assays and provided experimental training. DAS and

22 OZ performed the cellular metabolite quantitation. JMS ran the calculations predicting residue pKa values and performed the ML309 docking. AH aided in protein preparations and cellular studies. AAB performed the ITC experiments. DGI performed the pHinder algorithm and analyzed the results. CDS conceived the idea for the project, analyzed the pHinder algorithm results, performed the energy minimizations, and wrote the paper. All contributed to data analysis and manuscript editing and approved the final version of the manuscript.

Funding This work was funded by a Research Scholar Grant, RSG-19-075-01-TBE, from the American Cancer Society (CDS), National Institutes of Health R00 CA187594 (CDS), R01 CA197855 (DLB), SBP NCI Cancer Center Support Grant P30 CA030199 (OZ and DAS), National Institutes of Health R35GM119518, R01NS103906, and R03TR002908 (DGI), U54CA132384 (SDSU) & U54CA132379 (UC San Diego), MARC 5T34GM008303 (SDSU), and IMSD 5R25GM058906 (SDSU), and the California Metabolic Research Foundation (SDSU). The results shown here are in part based upon data generated by the TCGA Research Network: https://www.cancer.gov/tcga. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Acknowledgments The authors would like to thank Prof. Kun-Liang Guan for the HT1080 cell lines.

Competing interests The authors declare that they have no conflicts of interest with the entirety of this article.

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36 Tables

Table 1: Assessment of IDH1 catalysis upon varying pH. Kinetic parameters for the normal forward and reverse reactions catalyzed by WT IDH1 in varying pH and buffers are shown. Steady-state rates were derived from fitting plots of kobs versus substrate concentration with the Michaelis-Menten equation, with the standard error of the mean (S.E.M.) determined from the deviance from these hyperbolic fits. Data were obtained as described in Fig 2.

-1 -1 -1 IDH1 Buffer Reaction kcat, s Km, mM kcat/Km, mM s WT Bis-Tris, pH 6.2 Isocitrate → 20.0 ± 0.4 0.042 ± 0.004 (0.48 ± 0.05) × 103 αKG WT Bis-Tris, pH 6.5 Isocitrate → 23.1 ± 0.6 0.048 ± 0.006 (0.48 ± 0.06) × 103 αKG WT Bis-Tris, pH 7.0 Isocitrate → 32 ± 1 0.075 ± 0.009 (0.43 ± 0.05) × 103 αKG WT Tris, pH 7.2 Isocitrate → 39 ± 1 0.11 ± 0.01 (0.35 ± 0.03) × 103 αKG WT Tris, pH 7.5 Isocitrate → 40.4 ± 0.8 0.030 ± 0.003 (1.4 ± 0.1) × 103 αKG WT Tris, pH 7.8 Isocitrate → 35.4 ± 0.6 0.035 ± 0.003 (1.01 ± 0.09) × 103 αKG WT Tris, pH 8.0 Isocitrate → 38.3 ± 0.9 0.038 ± 0.004 (1.0 ± 0.1) × 103 αKG WT KPhos, pH 6.2 Isocitrate → 20.2 ± 0.4 0.027 ± 0.003 (0.75 ± 0.08) × 103 αKG WT KPhos, pH 6.5 Isocitrate → 23.0 ± 0.4 0.034 ± 0.003 (0.68 ± 0.06) × 103 αKG WT KPhos, pH 6.8 Isocitrate → 27.5 ± 0.6 0.040 ± 0.004 (0.69 ± 0.07) × 103 αKG WT KPhos, pH 7.0 Isocitrate → 31.7 ± 0.8 0.050 ± 0.006 (0.63 ± 0.08) × 103 αKG WT KPhos, pH 7.2 Isocitrate → 35.5 ± 0.8 0.060 ± 0.006 (0.59 ± 0.06) × 103 αKG

37 WT KPhos, pH 7.5 Isocitrate → 37.6 ± 0.7 0.061 ± 0.005 (0.62 ± 0.05) × 103 αKG WT KPhos, pH 7.8 Isocitrate → 40.0 ± 0.7 0.066 ± 0.005 (0.61 ± 0.05) × 103 αKG WT KPhos, pH 8.0 Isocitrate → 39.2 ± 0.7 0.067 ± 0.005 (0.59 ± 0.05) × 103 αKG WT Bis-Tris, pH 6.2 αKG → 1.6 ± 0.1 0.04 ± 0.01 40 ± 10 isocitrate WT Bis-Tris, pH 6.5 αKG → 3.2 ± 0.2 0.12 ± 0.04 27 ± 9 isocitrate WT Bis-Tris, pH 6.8 αKG → 3.3 ± 0.2 0.14 ± 0.03 24 ± 5 isocitrate WT Bis-Tris, pH 7.0 αKG → 3.8 ± 0.3 0.14 ± 0.04 27 ± 8 isocitrate WT Tris, pH 7.2 αKG → 3.4 ± 0.3 0.26 ± 0.07 13 ± 4 isocitrate WT Tris, pH 7.5 αKG → 3.6 ± 0.2 0.246 ± 0.06 15 ± 4 isocitrate WT KPhos, pH 6.2 αKG → 3.5 ± 0.3 0.6 ± 0.2 6 ± 2 isocitrate WT KPhos, pH 6.5 αKG → 4.1 ± 0.2 1.0 ± 0.1 4.1 ± 0.5 isocitrate WT KPhos, pH 6.8 αKG → 4.9 ± 0.2 0.65 ± 0.08 7.5 ± 0.1 isocitrate WT KPhos, pH 7.0 αKG → 4.1 ± 0.2 0.71 ± 0.09 5.8 ± 0.8 isocitrate WT KPhos, pH 7.2 αKG → 3.87 ± 0.07 0.28 ± 0.02 14 ± 1 isocitrate WT KPhos, pH 7.5 αKG → 3.8 ± 0.1 0.46 ± 0.05 8.3 ± 0.9 isocitrate WT KPhos, pH 7.8 αKG → 1.87 ± 0.08 0.87 ± 0.09 2.1 ± 0.2 isocitrate

38 Table 2: Metabolite assessment of cells with an acidic pHi. Cellular quantitation of metabolites related to IDH1 activity at varying pH, biological replicates of two.

6 Cell line Treatment pHi [Isocitrate], [αKG], [2HG], nmol/10 nmol/106 cells nmol/106 cells cells HT1080 (-/+++ No treatment 7.57 ± 0.04 0.050 ± 0.004 0.31 ± 0.08 0.070 ± 0.008 IDH1) + ESOM 7.39 ± 0.01 ≤ 0.01 0.20 ± 0.02 0.048 ± 0.005 HT1080 No treatment 7.52 ± 0.06 0.10 ± 0.02 0.39 ± 0.06 26.9 ± 0.7 (R132C/+ IDH1) + ESOM 7.31 ± 0.01 ≤ 0.01 0.14 ± 0.01 5.8 ± 0.2

Table 3: Kinetic parameters for the normal forward and neomorphic reactions catalyzed by IDH1 variants. Steady-state rates of kcat, Km, and kcat/Km were derived from fitting plots of kobs versus substrate concentration with the Michaelis-Menten equation, with the standard error determined from the deviance from these hyperbolic fits. Data were obtained as described in Fig 5.

-1 -1 -1 IDH1, reaction kcat, s Km, mM kcat/Km, mM s WT, 37.6 ± 0.7 0.061 ± 0.005 620 ± 50 isocitrate → αKG K217M, 42 ± 1 0.15 ± 0.02 280 ± 40 isocitrate → αKG K217Q, 28.7 ± 0.5 0.25 ± 0.02 115 ± 9 isocitrate → αKG D273N, 22 ± 1 19 ± 2 1.2 ± 0.1 isocitrate → αKG D273S, 15 ± 1 12 ± 3 1.3 ± 0.3 isocitrate → αKG D273L, 7.0 ± 0.2 1.9 ± 0.2 3.7 ± 0.4 isocitrate → αKG R132H, 1.44 ± 0.05a 1.5 ± 0.2a 1.0 ± 0.1a αKG → D2HG

39 D273N/R132H, ≤ 0.02b N.D.c N.D.c αKG → D2HG D273L/R132H, ≤ 0.02b N.D.c N.D.c αKG → D2HG D273S/R132H, ≤ 0.02b N.D.c N.D.c αKG → D2HG a From Ref. [115]. b No detectable activity (NADPH consumption) was observed, so a limit of detection is listed. Here, 500 nM of protein and 1-5 mM αKG was used. c Due to no detectable activity, Km and kcat/Km values could not be determined (N.D., not determined).

40 Figure legends

Figure 1. Reactions catalyzed by IDH1. The normal and neomorphic reactions catalyzed by WT (A) and mutant (B) IDH1.

Figure 2. Effects of pH and buffer on WT IDH1 catalysis. Steady-state rates of the forward reaction, the conversion of isocitrate to αKG, catalyzed by WT IDH1 were measured as function of varying pH using either Tris (pH 7.2-8.0) or bis-Tris (pH 6.2-7.0) buffers (A), or KPhos buffer (B). Steady-state rates of the reverse reaction, the conversion of αKG to isocitrate, catalyzed by WT IDH1 were measured as a function of varying pH using either Tris or bis-Tris buffers (C), or KPhos buffer (D). In (A-D), at least two protein preparations were used to measure the observed rate constants (kobs) at varying substrate concentrations, which were calculated from determining the linear portion of plots of concentration versus time. Each point in the curve represents a single replicate.

The variation in kcat (E), Km (F), and kcat/Km (efficiency) (G) due to change in pH from parts (A-D) is shown.

Figure 3. Change in IDH1-related metabolites upon pHi modification. Two sets of cell lines were used: patient-derived HT1080 cells, which contain an endogenous heterozygous R132C IDH1 mutation (R132C/+ IDH1), or HT1080 cells where the R132C IDH1 allele was ablated with a T77A mutation to destroy neomorphic activity (αKG to D2HG production) in the R132C allele, and made to stably overexpress WT IDH1 (-/+++ IDH1) [80]. Cell lines were either untreated or treated with 200 µM ESOM to decrease the pHi. The resulting change in pH are shown in (A). Experiments were performed as technical triplicates. (B) Metabolites were then quantified and changes in isocitrate, αKG, and 2HG (isomers unresolved) are highlighted (see Table S1 for additional metabolites). Experiments were performed as biological duplicates. Not significant (ns) p > 0.05, *p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001.

Figure 4. pHinder analysis of the holo IDH1 dimer. (A) Networks of buried ionizable residues were identified using pHinder in a previously solved structure of holo WT IDH1

41 bound to NADP+, isocitrate, and Ca2+ (1T0L [72]). These networks are shown as grey lines and with the residues making up this network shown as purple (chain A) or grey (chain B) sticks. (B) Only the residues involved in this network, as well as isocitrate and NADP+ (shown in green) are highlighted. (C) The location of K217 (chain A) and K217’ (chain B) relative to the active sites. (D) The location of D273 (chain A) and D273’ (chain B) relative to the active sites. (E) pHinder was also used to identify a network of buried ionizable residues in a previously solved structure of holo R132H IDH1 bound to αKG, NADP+, and Ca2+ (4KZO [64]). For clarity, only residues described in the text as being part of networks involving K212 and D273 are labeled in part B and E. (F) Two ML309 ligands [81] were docked into the density present in a cryo-EM structure of R132C IDH1 incubated with ML309 [116], and the localization of D273 relative to these inhibitors is shown.

Figure 5. Kinetic characterization of K217 and D273 mutants in the WT IDH1 background. Steady-state rates of the normal forward reaction, the conversion of isocitrate to αKG, as catalyzed by (A) K217Q and K217M IDH1, and (B) D273N, D273S, and D273L IDH1 are shown relative to WT IDH1. kobs values were obtained as described in Fig. 2. Replicates were performed for higher concentrations of isocitrate in the case of D273S IDH1 as these measurements proved more error prone. (C) Comparison of sensitivity to pH of the normal forward reaction in D273L and WT IDH1. Four representative pH values were tested. No pH sensitivity was observed in the reaction catalyzed by D273L IDH1 for all pH values found in the physiological pH range. In contrast, WT IDH1 catalysis was sensitive changes in pH at all pH ranges tested. Each point in the curve represents a single replicate, and at least two different protein preparations were used to obtain replicates in the curves.

42

An acidic residue buried in the dimer interface of isocitrate dehydrogenase 1 (IDH1) helps regulate catalysis and pH sensitivity

Lucas A. Luna1, Zachary Lesecq1, Katharine A. White2, An Hoang1, David A. Scott3, Olga Zagnitko3, Andrey A. Bobkov3, Diane L. Barber4, Jamie M. Schiffer5, Daniel G. Isom6, and Christal D. Sohl1,‡,§

1Department of Chemistry and Biochemistry, San Diego State University, San Diego, CA, 92182 2Harper Cancer Research Institute, Department of Chemistry and Biochemistry, University of Notre Dame, South Bend, IN, 46617 3Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, 92037 4Department of Cell and Tissue Biology, University of California, San Francisco, CA, 94143 5Janssen Research and Development, 3210 Merryfield Row, San Diego, CA, 92121 6Department of Pharmacology, Sylvester Comprehensive Cancer Center, and Center for Computational Sciences, University of Miami, Miami, FL, 33136

Running title: Mechanisms of pH-dependent IDH1 catalysis

‡Correspondence: Christal D. Sohl, Department of Chemistry and Biochemistry, San Diego State University, CSL 328, 5500 Campanile Dr., San Diego, California 92182, Email: [email protected]; Telephone: (619) 594-2053.

§This paper is dedicated to the memory of our dear colleague and friend, Michelle Evon Scott (1990-2020).

Supporting information content: Figure S1 Figure S2 Figure S3 Figure S4 Figure S5 Figure S6 Table S1 Table S2 References

1

Figure S1. (A) WT and D273L IDH1 purified from Ni-NTA affinity resin were assessed using size exclusion chromatography (SEC) to ensure protein was primarily found in the dimer form (~97 kDa dimer, elution peak at fraction 75 mL). Protein concentration for the WT IDH1 dimer is higher than the D273L IDH1 dimer because twice the volume of bacterial culture volume was used during heterologous expression of WT IDH1. (B) Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) analysis of IDH1 to assess protein purity (4-20% TGX Stain-free gel). FT: column flow-through.

2

Figure S2. Circular dichroism (CD) was used to assess secondary structure and obtain Tm values. Tm values for WT IDH1 in KPhos buffer were determined to be as follows: 48.9 ± 0.1 °C (pH 6.2), 49.0 ± 0.1 °C (pH 6.5), 48.7 ± 0.1°C (pH 6.8), 48.61 ± 0.08 °C (pH 7.0), 48.7 ± 0.1 °C (pH 7.2), 48.35 ± 0.09 °C (pH 7.5), 47.99 ± 0.08 °C (pH 7.8), 47.66 ± 0.08 °C (pH 8.0).

3

Figure S3. ESOM treatment was selected for its ability to robustly alter pH yet minimize cell death. Trypan blue was used to assess live versus dead cells 16 h after ESOM treatment (200 µM final concentration). Comparisons of cell viability for WT (-/+++ IDH1) and R132C (R132C/+ IDH1) IDH1 cells [1], both ESOM-treated (+ ESOM) and untreated (- ESOM), are shown. Percent viability is as follows: HT1080 WT - ESOM: 97.7%; HT1080 WT + ESOM: 97.8%; HT1080 R132C - ESOM: 98.4%; HT1080 R132C + ESOM: 98.4%.

4

Figure S4. pHinder analysis of the apo IDH1 dimer. (A) Networks of buried ionizable residues in a previously solved structure of apo WT IDH1 bound to NADP+ (1T09 [2]) were identified. Residues involved in these networks are shown in stick form (blue in chain A, grey in chain B), and connected with grey lines. (B) An overlay of the networks identified in apo IDH1 (blue residues, with the protein also shown in cartoon, 1T09 [2]), and holo IDH1 (green residues, 1T0L [2]). NADP+ molecules are shown as lines. (C) Highlight of the ionizable residue networks found in apo WT IDH1 (1T09 [2]). For clarity, only the residues cited in the main text as being part of networks involving K212 and K273 are labeled.

5

Figure S5. Circular dichroism (CD) was used to compare secondary structure and Tm values between WT and D273L IDH1. Tm values in KPhos buffer at pH 7.5 were determined to be as follows: 48.35 ± 0.09 °C (WT IDH1), 49.44 ± 0.08 °C (D273L IDH1).

6

Figure S6. Structural models of the D273 mutant series. (A) The orientation of IDH1 as shown in parts B-D, with color schemes indicated for the modeled D273N, D273S, D273L in the WT IDH1 holo (1T0L [2]) and WT IDH1 apo (1T09 [2]) backgrounds. Previously solved structures of apo WT IDH1[2], holo IDH1[2], and C132H IDH1 [3] with ML309 docked (5K11 [3]) are also shown. We previously modeled the histidine mutation at residue 132 using a structure of R132C IDH1, and so denote this change as C132H IDH1. (B) Energy-minimized models of D273N, D273S, and D273L IDH1 generated in the WT IDH1 holo structure (αKG, NADP+, and Ca2+ bound, 1T0L [2]) aligned with apo [2] and holo [2] WT IDH1. (C) Energy-minimized models of D273N, D273S, and D273L IDH1 generated in the WT IDH1 apo structure (NADP+ bound, 1T09 [2]) aligned with apo [2] and holo [2] WT IDH1. (D) Energy-minimized models of D273N, D273S, D273L IDH1 generated in the WT IDH1 apo structure (NADP+ bound, 1T09 [2]) aligned with apo WT IDH1 apo [2] and C132H IDH1 with ML309 docked in the inhibitor binding pocket [3].

7

Table S1. Absolute quantitation of cell metabolites in HT1080 cells. Patient-derived HT1080 cells, which contain an endogenous heterozygous R132C IDH1 mutation were used as is (R132C/+ IDH1) or the R132C IDH1 allele was ablated with a T77A mutation to destroy neomorphic (αKG to D2HG) activity in the R132C allele, and made to stably overexpress WT IDH1 (-/+++ IDH1) [1]. To modulate pHi, cell lines received no treatment or were treated with 200 µM ESOM, which decreases the pHi from 7.58 ± 0.04 to 7.39 ± 0.01 (HT1080 -/+++ IDH1), or 7.52 ± 0.06 to 7.31 ± 0.01 (HT1080 R132C/+ IDH1). A norvaline standard was used to quantify each metabolite in the whole cell lysates [4, 5]. These experiments were repeated in duplicate, with averages +/- SD (standard deviation) shown.

HT1080 HT1080 HT1080 HT1080 (-/+++ R132C/+ (-/+++ IDH1) (R132C/+ IDH1) + no IDH1) + Metabolite SD + ESOM, SD IDH1) + no SD SD treatment, ESOM, nmol/106 treatment, nmol/106 nmol/106 cells nmol/106 cells cells cells 2HG 0.07 0.01 0.05 0.00 26.85 0.73 5.76 0.20 3PG 0.62 0.18 0.67 0.19 1.40 0.45 1.20 0.06 GABA 0.06 0.09 0.05 0.01 0.22 0.02 0.05 0.01 Lactate 10.42 1.67 8.52 2.14 16.00 3.80 9.95 0.33 α- 0.31 0.08 0.20 0.02 0.39 0.06 0.14 0.01 Ketoglutarate Alanine 2.50 0.19 3.95 0.52 5.02 0.44 4.40 0.04 Asparagine 0.52 0.00 0.76 0.12 1.21 0.07 0.92 0.06 Aspartate 1.70 0.28 1.19 0.47 3.71 0.08 1.34 0.04 Beta-alanine 1.38 0.18 1.09 0.30 2.06 0.15 1.02 0.02 Citrate 0.60 0.00 0.18 0.01 1.10 0.03 0.16 0.03 Cysteine 1.24 0.04 2.61 0.18 1.88 0.23 2.79 0.26 DHAP 60.63 35.21 75.33 41.88 111.42 34.16 149.14 19.31 Fumarate 0.34 0.03 0.11 0.03 0.61 0.03 0.13 0.00 Glutamate 39.05 1.24 41.76 7.41 66.41 5.03 44.46 0.81 Glutamine 34.22 4.75 56.07 5.95 57.20 9.11 48.61 7.41 Glycerol_P(1) 0.54 0.06 1.13 0.25 1.43 0.24 1.98 0.15 Glycerol_P(2) 0.37 0.07 0.73 0.15 0.92 0.22 1.25 0.10 Glycine 14.93 2.33 17.84 4.96 25.45 1.69 18.49 0.51

Hydroxyproline 0.20 0.01 0.24 0.02 0.37 0.01 0.35 0.05

Isocitrate 0.05 0.00 0.00 0.00 0.10 0.02 0.01 0.00 Isoleucine 4.54 0.04 10.49 0.02 9.30 0.09 10.72 0.05 Leucine 4.08 0.02 9.26 0.22 8.29 0.06 9.84 0.39 Lysine 0.94 0.06 1.94 0.18 1.89 0.11 2.26 0.03 Malate 0.70 0.01 0.28 0.07 1.06 0.13 0.25 0.02 Methionine 1.65 0.02 3.94 0.04 3.26 0.04 4.03 0.01

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Ornithine 0.14 0.01 0.26 0.04 0.29 0.02 0.31 0.02 Phenylalanine 3.05 0.03 6.57 0.24 5.96 0.22 6.80 0.14 PEP 0.18 0.03 0.22 0.02 0.39 0.06 0.30 0.03 Proline 1.19 0.02 0.37 0.07 1.49 0.07 0.40 0.02 Pyruvate 1.44 0.68 1.26 0.48 2.58 0.41 0.84 0.10 Serine 3.44 0.46 6.18 1.29 6.25 0.55 7.04 0.04 Succinate 0.05 0.02 0.04 0.00 0.09 0.00 0.04 0.01 Threonine 20.98 5.28 32.53 9.16 40.37 1.84 31.95 1.36 Tryptophan 1.61 0.17 3.23 0.46 3.12 0.35 3.38 0.16 Tyrosine 2.76 0.08 5.64 0.42 5.51 0.29 6.01 0.05 Urea 0.26 0.10 0.23 0.07 0.33 0.05 0.38 0.18 Valine 4.25 0.06 9.54 0.36 8.68 0.43 10.18 0.10

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Table S2. Calculated pKa values for 1T0L [2] (holo WT IDH1) using PROPKA [6, 7]. pH pKa pH pKa pH pKa pH pKa pH pKa MET1A 7.91 GLU110A 5.72 LYS233A 10.8 GLU365A 4.32 GLU62B 3.73 LYS3A 9.5 CYS114A 11.64 TYR235A 11.46 GLU368A 3.98 LYS65B 11.28 LYS4A 10.43 LYS115A 10.77 LYS236A 10.75 LYS374A 10.55 LYS66B 10.41 GLU12A 4.1 ARG119A 11.83 GLU240A 4.39 ASP375A 1.01 HID67B1 5.31 ASP16A 5.32 LYS126A 11.47 LYS243A 10.45 CYS379A 11.94 LYS72B 8.96 GLU17A 3.51 ARG132A 14.55 TYR246A 13.99 LYS381A 10.59 CYS73B 11.89 ARG20A 13.68 HID133A 3.12 GLU247A 4.93 ARG388A 13.96 ASP79B 1.9 GLU24A 4.68 TYR135A 13.8 HID248A 2.64 ASP390A 3.24 GLU80B 4.84 LYS27A 11.85 ASP137A 5.52 ARG249A 11.88 TYR391A 10.22 LYS81B 9.92 GLU28A 4.56 TYR139A 9.84 ASP253A 4.66 GLU396A 3.47 ARG82B 12 LYS29A 9.93 ARG140A 13.19 LYS260A 12.39 ASP399A 3.62 GLU84B 4.49 TYR34A 11.24 ASP143A 5.03 GLU262A 3.53 LYS400A 10.22 GLU85B 4.54 GLU36A 4.58 LYS151A 10.56 CYS269A 14.06 GLU403A 4.61 LYS87B 10.04 ASP38A 3.16 GLU153A 4.62 LYS270A 12.69 LYS406A 10.64 LYS89B 10.14 HID40A 6.5 TYR156A 10.85 TYR272A 9.84 LYS408A 12.05 LYS93B 9.36 TYR42A 10.73 ASP160A 2.7 ASP273A 6.59 LYS413A 10.16 ARG100B 12 ASP43A 3 LYS164A 10.49 ASP279A 5.23 LEU414A 3.39 ARG109B 10.71 GLU47A 4.77 TYR167A 11.11 TYR285A 13.08 MET1B 7.33 GLU110B 5.66 ARG49A 11.49 HID170A 4.29 CYS297A 12.29 LYS3B 10.25 CYS114B 11.54 ASP50A 2.77 GLU173A 4.65 ASP299A 2.64 LYS4B 10.46 LYS115B 10.77 ASP54A 5.13 GLU174A 4.79 LYS301A 10.41 GLU12B 3.9 ARG119B 11.85 LYS58A 10.47 TYR183A 10.77 GLU304A 7.52 ASP16B 4.92 LYS126B 11.35 ASP59A 3.42 ASP186A 4.33 GLU306A 3.65 GLU17B 3.74 ARG132B 14.17 GLU62A 3.73 LYS187A 11.26 HID309A 3.75 ARG20B 14.41 HID133B 3.12 LYS65A 11.28 GLU190A 5.31 ARG314A 12 GLU24B 4.96 TYR135B 11.2 LYS66A 10.39 ASP191A 4.49 HID315A 7.63 LYS27B 11.86 ASP137B 5.36 HID67A 5.29 HID194A 6.35 TYR316A 11.16 GLU28B 4.59 TYR139B 9.84 LYS72A 8.85 LYS203A 10.35 ARG317A 12.87 LYS29B 10.48 ARG140B 11.9 CYS73A 12.07 TYR208A 10.57 TYR319A 10.33 TYR34B 11.41 ASP143B 5.55 ASP79A 2.5 LYS212A 14.15 LYS321A 10.45 GLU36B 4.31 LYS151B 10.3 GLU80A 4.7 LYS217A 7.97 GLU324A 4.13 ASP38B 2.81 GLU153B 4.92 LYS81A 10.07 LYS218A 10.49 ARG338A 12.71 HID40B 6.45 TYR156B 11.07 ARG82A 14.45 TYR219A 9.84 HID342A 5.74 TYR42B 10.82 ASP160B 2.62 GLU84A 4.48 ASP220A 3.99 ARG343A 12.65 ASP43B 3.47 LYS164B 10.21 GLU85A 4.03 ARG222A 13.19 LYS345A 10.38 GLU47B 6.94 TYR167B 10.99 LYS87A 10.44 LYS224A 10.76 ASP347A 3.23 ARG49B 11.8 HID170B 4.01 LYS89A 10.35 ASP225A 5.31 LYS350A 10.29 ASP50B 4.13 GLU173B 4.62 LYS93A 9.6 GLU229A 4.16 GLU351A 4.03 ASP54B 5.15 GLU174B 4.75 ARG100A 12 TYR231A 11.72 GLU360A 5.15 LYS58B 10.45 TYR183B 14.01 ARG109A 10.68 ASP232A 4.19 GLU361A 3.82 ASP59B 3.44 ASP186B 4.26 10 pH pKa pH pKa pH pKa pH pKa pH pKa LYS187B 11.37 HID309B 3.74 ARG20C 14.55 HID133C 3.15 GLU247C 4.93 GLU190B 5.36 ARG314B 12 GLU24C 5.06 TYR135C 10.75 HID248C 2.72 ASP191B 4.52 HID315B 7.31 LYS27C 11.87 ASP137C 6.05 ARG249C 11.87 HID194B 6.33 TYR316B 13.77 GLU28C 4.39 TYR139C 9.84 ASP253C 4.47 LYS203B 10.34 ARG317B 12.83 LYS29C 10.16 ARG140C 12.66 LYS260C 12.01 TYR208B 10.54 TYR319B 12.71 TYR34C 11.12 ASP143C 5.08 GLU262C 3.59 LYS212B 14.13 LYS321B 10.4 GLU36C 4.55 LYS151C 10.5 CYS269C 14.04 LYS217B 8.24 GLU324B 5.16 ASP38C 3.31 GLU153C 4.71 LYS270C 12.71 LYS218B 10.5 ARG338B 12.93 HID40C 6.66 TYR156C 11.07 TYR272C 9.84 TYR219B 9.84 HID342B 5.72 TYR42C 10.75 ASP160C 2.57 ASP273C 6.4 ASP220B 3.98 ARG343B 12.38 ASP43C 2.94 LYS164C 10.13 ASP279C 5.24 ARG222B 13.21 LYS345B 10.3 GLU47C 6.52 TYR167C 11.16 TYR285C 13.09 LYS224B 10.5 ASP347B 3.66 ARG49C 11.71 HID170C 4 CYS297C 12.26 ASP225B 5.23 LYS350B 10.53 ASP50C 3.9 GLU173C 4.7 ASP299C 2.26 GLU229B 4.17 GLU351B 4.37 ASP54C 5.1 GLU174C 4.59 LYS301C 10.52 TYR231B 11.69 GLU360B 4.61 LYS58C 10.47 TYR183C 13.82 GLU304C 7.57 ASP232B 4.13 GLU361B 3.8 ASP59C 3.43 ASP186C 4.71 GLU306C 3.97 LYS233B 10.79 GLU365B 4.34 GLU62C 3.73 LYS187C 11.26 HID309C 3.78 TYR235B 11.45 GLU368B 3.86 LYS65C 11.3 GLU190C 5.33 ARG314C 12 LYS236B 10.77 LYS374B 10.55 LYS66C 10.4 ASP191C 4.5 HID315C 7.78 GLU240B 4.38 ASP375B 1.17 HID67C 5.24 HID194C 6.36 TYR316C 12.92 LYS243B 10.46 CYS379B 11.99 LYS72C 8.9 LYS203C 10.34 ARG317C 12.94 TYR246B 13.98 LYS381B 10.6 CYS73C 11.98 TYR208C 10.54 TYR319C 9.84 GLU247B 4.92 ARG388B 13.39 ASP79C 1.87 LYS212C 13.46 LYS321C 10.36 HID248B 2.64 ASP390B 3.22 GLU80C 4.8 LYS217C 8.16 GLU324C 4.94 ARG249B 11.86 TYR391B 10.36 LYS81C 10.03 LYS218C 10.48 ARG338C 12.29 ASP253B 5.72 GLU396B 3.69 ARG82C 14.88 TYR219C 9.84 HID342C 5.63 LYS260B 12.35 ASP399B 3.39 GLU84C 4.49 ASP220C 3.99 ARG343C 12.13 GLU262B 3.67 LYS400B 10.24 GLU85C 4.41 ARG222C 13.2 LYS345C 10.35 CYS269B 14.05 GLU403B 4.51 LYS87C 10.07 LYS224C 10.67 ASP347C 3.75 LYS270B 12.73 LYS406B 10.55 LYS89C 10.29 ASP225C 5.21 LYS350C 10.4 TYR272B 9.84 LYS408B 12.01 LYS93C 9.64 GLU229C 4.18 GLU351C 4.52 ASP273B 6.4 LYS413B 10.42 ARG100C 12 TYR231C 11.7 GLU360C 5.52 ASP279B 4.08 LEU414B 3.4 ARG109C 10.79 ASP232C 4.14 GLU361C 3.93 TYR285B 13.08 MET1C 7.84 GLU110C 5.71 LYS233C 10.8 GLU365C 4.3 CYS297B 12.21 LYS3C 10.55 CYS114C 11.72 TYR235C 11.46 GLU368C 3.98 ASP299B 2.24 LYS4C 10.37 LYS115C 10.78 LYS236C 10.76 LYS374C 10.55 LYS301B 10.39 GLU12C 3.79 ARG119C 11.82 GLU240C 4.39 ASP375C 1.19 GLU304B 8.21 ASP16C 4.84 LYS126C 11.42 LYS243C 10.46 CYS379C 11.98 GLU306B 3.76 GLU17C 3.57 ARG132C 14.27 TYR246C 13.97 LYS381C 10.61

11 pH pKa pH pKa pH pKa pH pKa ARG388C 13.8 ASP79D 2.31 LYS212D 13.61 LYS321D 10.34 ASP390C 3.15 GLU80D 4.74 LYS217D 8 GLU324D 4.32 TYR391C 10.25 LYS81D 10.09 LYS218D 10.5 ARG338D 13.75 GLU396C 3.73 ARG82D 14.31 TYR219D 9.84 HID342D 5.71 ASP399C 3.5 GLU84D 4.47 ASP220D 3.99 ARG343D 12.03 LYS400C 11.2 GLU85D 3.62 ARG222D 13.23 LYS345D 10.3 GLU403C 3.62 LYS87D 10.43 LYS224D 10.78 ASP347D 3.86 LYS406C 10.41 LYS89D 10.34 ASP225D 5.37 LYS350D 10.58 LYS408C 12.19 LYS93D 9.68 GLU229D 4.16 GLU351D 3.87 LYS413C 9.99 ARG100D 12 TYR231D 11.69 GLU360D 3.79 LEU414C 3.37 ARG109D 10.96 ASP232D 4.19 GLU361D 3.88 MET1D 7.91 GLU110D 5.72 LYS233D 10.81 GLU365D 4.6 LYS3D 10.52 CYS114D 11.66 TYR235D 11.44 GLU368D 3.94 LYS4D 10.41 LYS115D 10.77 LYS236D 10.75 LYS374D 10.56 GLU12D 3.88 ARG119D 11.83 GLU240D 4.4 ASP375D 1.3 ASP16D 5.38 LYS126D 11.47 LYS243D 10.46 CYS379D 12.02 GLU17D 4.15 ARG132D 14.22 TYR246D 13.97 LYS381D 10.59 ARG20D 13.55 HID133D 3.07 GLU247D 4.81 ARG388D 14.14 GLU24D 4.42 TYR135D 13.8 HID248D 2.6 ASP390D 3.27 LYS27D 11.87 ASP137D 5.29 ARG249D 11.87 TYR391D 10.35 GLU28D 4.74 TYR139D 9.84 ASP253D 6 GLU396D 3.04 LYS29D 10.57 ARG140D 13.22 LYS260D 12.33 ASP399D 3.12 TYR34D 11.37 ASP143D 5.26 GLU262D 3.54 LYS400D 10.41 GLU36D 4.47 LYS151D 10.24 CYS269D 14.03 GLU403D 4.5 ASP38D 2.86 GLU153D 4.88 LYS270D 12.75 LYS406D 10.38 HID40D 6.51 TYR156D 11.01 TYR272D 9.84 LYS408D 12.01 TYR42D 10.77 ASP160D 2.63 ASP273D 6.59 LYS413D 9.74 ASP43D 3.26 LYS164D 10.45 ASP279D 5.46 LEU414D 3.46 GLU47D 4.78 TYR167D 10.56 TYR285D 13.09 ARG49D 11.54 HID170D 4.26 CYS297D 12.41 ASP50D 2.78 GLU173D 4.66 ASP299D 2.27 ASP54D 5.15 GLU174D 4.59 LYS301D 10.41 LYS58D 10.48 TYR183D 10.83 GLU304D 8.14 ASP59D 3.41 ASP186D 4.25 GLU306D 3.65 GLU62D 3.74 LYS187D 11.26 HID309D 3.81 LYS65D 11.27 GLU190D 5.32 ARG314D 12 LYS66D 10.41 ASP191D 4.53 HID315D 7.72 HID67D 5.27 HID194D 6.39 TYR316D 10.99 LYS72D 8.97 LYS203D 10.33 ARG317D 12.92 CYS73D 12.06 TYR208D 10.57 TYR319D 10.23 1 This program uses the abbreviation “Hid” for histidine. 12

References

1 Ma, S., Jiang, B., Deng, W., Gu, Z. K., Wu, F. Z., Li, T., Xia, Y., Yang, H., Ye, D., Xiong, Y. and Guan, K. L. (2015) D-2-hydroxyglutarate is essential for maintaining oncogenic property of mutant IDH-containing cancer cells but dispensable for cell growth. Oncotarget. 6, 8606-8620 2 Xu, X., Zhao, J., Xu, Z., Peng, B., Huang, Q., Arnold, E. and Ding, J. (2004) Structures of human cytosolic NADP-dependent isocitrate dehydrogenase reveal a novel self-regulatory mechanism of activity. J Biol Chem. 279, 33946-33957 3 Merk, A., Bartesaghi, A., Banerjee, S., Falconieri, V., Rao, P., Davis, M. I., Pragani, R., Boxer, M. B., Earl, L. A., Milne, J. L. and Subramaniam, S. (2016) Breaking Cryo-EM resolution barriers to facilitate drug discovery. Cell. 165, 1698-1707 4 Ratnikov, B., Aza-Blanc, P., Ronai, Z. A., Smith, J. W., Osterman, A. L. and Scott, D. A. (2015) Glutamate and asparagine cataplerosis underlie glutamine addiction in melanoma. Oncotarget. 6, 7379-7389 5 Avellaneda Matteo, D., Grunseth, A. J., Gonzalez, E. R., Anselmo, S. L., Kennedy, M. A., Moman, P., Scott, D. A., Hoang, A. and Sohl, C. D. (2017) Molecular mechanisms of isocitrate dehydrogenase 1 (IDH1) mutations identified in tumors: The role of size and hydrophobicity at residue 132 on catalytic efficiency. J Biol Chem. 292, 7971-7983 6 Sastry, G. M., Adzhigirey, M., Day, T., Annabhimoju, R. and Sherman, W. (2013) Protein and ligand preparation: parameters, protocols, and influence on virtual screening enrichments. J Comput Aided Mol Des. 27, 221-234 7 Schrödinger Release 2018-3, Schrödinger Suite 2018-3 Protein Preparation Wizard.

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